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Review

Bibliometric Study of Scientific Production on the Term Collaborative Learning in Web of Science

by
Antonio-José Moreno-Guerrero
1,*,
Pedro Jurado de los Santos
2,
María Luisa Pertegal-Felices
3 and
Rebeca Soler Costa
4
1
Department of Didactics and School Organization, University of Granada, 18001 Granada, Spain
2
Department of Applied Pedagogy, Autonomous University of Barcelona, 08193 Barcelona, Spain
3
Developmental and Educational Psychology Department, University of Alicante, 03690 Alicante, Spain
4
Department of Educational Sciences, University of Zaragoza, 50009 Zaragoza, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(14), 5649; https://0-doi-org.brum.beds.ac.uk/10.3390/su12145649
Submission received: 9 June 2020 / Revised: 9 July 2020 / Accepted: 10 July 2020 / Published: 14 July 2020
(This article belongs to the Special Issue Sustainable Development Goals (SDGs): The Challenges of the 2020-2030s for Quality Education)
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Abstract

:
Currently, more and more teachers decide to follow active teaching methods, leaving behind traditional teaching methods. Among the most used pedagogical methods in the educational field is the collaborative learning. The general objective of the present investigation is to know the performance and academic development of the term "collaborative learning" in the documents collected in the Web of Science database. The research method developed was based on a bibliometric study, identifying academic performance and conceptual development, through a co-word analysis. Particularly, we have pursued four main objectives: (a) To determine the degree of performance of documents collected from collaborative learning; (b) to identify the scientific development of so-called collaborative learning; (c) to analyze the most incidental aspects of collaborative learning; and (d) to value the most representative authors who are experts in the use of collaborative learning. The total number of manuscripts studied is 3295. The results show the manuscripts are written mainly in English by researchers who belong from the United States. The main area of knowledge is Education Educational Research. As a conclusion, it can be said that the collaborative learning pedagogical method is at a turning point in the scientific field. Its scientific evolution, focused on its principles in the students themselves, has extended to other branches. At present, studies are oriented towards technological resources, co-regulation, and the academic achievements of students. Furthermore, in the coming years the terms innovation, design, patterns, collaboration, and communication will probably be the new lines of study in this scientific field.

1. Theoretical Background

Roughly speaking, globalization has led to developments in various social areas [1]. In turn, this evolution has not only had consequences in the economic, political, or social spheres; in the educational sphere, the implementation of innovation processes in the different educational institutions has also experienced a great evolution [2]. In order to update and offer quality and innovative training, it is necessary to abandon traditional teaching–learning approaches [3], as well as passive training methods [4]. For this reason, the line of action in the educational and pedagogical field must be directed towards the development of new innovative practices. This can have a positive influence on the overall development of students [5,6,7,8,9,10], increasing their motivation and satisfaction [11]. However, the inclusion of these innovative practices in the teaching–learning processes requires an effort and coordination of all the players involved. This implies both teachers [12] and those agents involved in managing educational institutions [13]. It is essential to begin by rethinking teaching processes [14], where information and communication technologies (ICT) facilitate the development and application of innovative teaching methods [15,16].
Currently, the lines of pedagogical innovation [17,18,19] focus on different educational aspects, among which the so-called collaborative teaching methods receive greater attention. This educational practice has become one of the most widely used methods in the field of education [20], since they allow a high educational potential to be achieved [21]. Considering the needs to be worked on and the evolution of society and education, collaborative learning is a method of teaching that occurs through the interaction of two or more people [22] who share certain resources at certain moments of their learning [23]. It may be necessary to bring into play the different skills of the group members [24] in order to achieve improvements in academic performance through the relationship between individuals [25], the exchange of experiences [26], or the change of roles among group members [27]. It should not be forgotten that the actions of the group members affect the acquisition of the educational objectives of the other components of the group [28]. In general terms, collaborative learning requires a group project [29], teamwork for problem solving [30], pedagogical debates [31], and work teams [32].
Some research shows that established social relationships do not appear at the time of learning but require a period of adaptation to achieve it adequately [33]. Clearly, an updated teacher training is essential [34] to provide pre-service teachers with the necessary didactic and methodological tools to be able to face new learning situations and assume and put into practice their life-long learning processes. In this sense, some limitations or disadvantages of this method would be the possible lack of involvement among students in the group [35]. This aspect must be taken into account if the training process is to be successful [36] and highly coordinated. Any didactic process always requires a previous didactic planning and a coordination of all its members to achieve the best results [37].
Among the advantages shown by recent research is that the teaching and learning process based on collaborative learning is positively valued by students [38,39], improves their interactions and communications [40,41], promotes communication among equals, increases their attitude [42], motivation [43], sense of community [44,45], the realization of pedagogical exercises [46], the mental situation of the student [47], and autonomy [48], actively involving him in his pedagogical acts to improve his interaction [49]. Some authors indicate that this method can contribute to improve students’ behavior and attitudes, and can influence their monitoring of learning [50,51]. In turn, it allows the creation of monitored teaching–learning situations where group reactions, the type of adaptive regulation and behavior can be analyzed (monitoring target, valence, and phase). This method allows the creation of opportunities and limitations in the different monitoring dimensions [28,52,53].
It is essential to always create a good learning environment, a social climate in the classroom that allows the student to feel at ease. Collaborative learning also contributes to regulation. Thus, the student has more tools to face the challenges of learning, participating in different didactic situations. This allows them to learn to manage their attitudes and emotions [54]. Collaborative learning also presents enormous advantages in relation to its use with digital competence, that is, the use of educational technologies [55]. It favors socialization and social interaction processes, the student’s satisfaction in learning acquisition, and promotes the use of innovative didactic models that confer a leading role to students. Even in learning environments where the use of Google Docs is prevalent, it is considered a good method [56,57,58,59].
On the other hand, some authors indicate that this method also favors intercultural competence by promoting collaborative learning environments with heterogeneous groups of students [60]. Traditional teaching–learning approaches do not allow for a focus on improving certain skills in the student training process. An example derived from recent research [61] shows that the collaborative learning allows for the articulation of the so-called buzz groups, thus improving the effectiveness of the student-centered approach. This also contributes to improving the student’s motivation by sharing their centers of interest. Innovation, the development of processes of creativity, critical thinking, and problem-solving allow for the development of collaborative learning together with experiential learning [62,63]. Other research indicates that this method has been beneficial for improving reading comprehension. Collaborative learning allows the development of didactic strategies that have a high positive impact on students, such as the use of peer collaboration in the analysis of complex texts [64].
In addition, it should be noted that studies indicate that the collaborative learning method favors sustainability, especially if this method is developed digitally [65] In addition, collaborative learning, associated with specific sustainability programs such as the European Project Semester (EPS), promotes multicultural and multidisciplinary teamwork, communication, problem solving, creativity, leadership, entrepreneurship, ethical reasoning, and global contextual analysis [66]. The collaborative learning method has been applied in the training of students of various kinds, especially students of interior design [67], administrative studies [68], or agro-food systems [69], with a view to sustainable development.

2. Justification and Objectives

The innovative topic we deal with in this paper is the so-called “collaborative learning”. Current theories prove it to be successful and spread in different research areas. In fact, it has been analyzed in the documents collected in the Web of Science (WoS). That analysis has allowed us to carry out a scientific mapping. To achieve this objective, different bibliometric indicators were analyzed, as well as the study of the performance and evolution of the term. However, we have also considered other documents in the Journal Citation Reports [70,71,72]. Hence, we provide updated models to contribute to the dissemination of knowledge.
The overall objective of this study is to identify the performance and conceptual development of "collaborative learning" in the documents collected in WoS. This formulation of the objective of the research and its creation arises from the fact that there are not enough studies developed using this bibliometric technique of documentary analysis. The aim of this study is to show researchers the new findings regarding this use of the term “collaborative learning”. In this way, the knowledge researchers require in this field are covered.
Particularly, four objectives were formulated in this research: (a) To determine the degree of performance of documents collected from collaborative learning; (b) to identify the scientific development of so-called collaborative learning; (c) to analyze the most incidental aspects of collaborative learning; (d) to value the most representative authors who are experts in the use of collaborative learning.
As research questions, the following issues are established: What is the academic performance of the term collaborative learning in the scientific production of Web of Science? What is the scientific evolution and the most relevant topics in the research developed on collaborative learning in Web of Science?

3. Method of Investigation

3.1. Structure of the Investigation

Once the objectives of the research were established, the methodology to be adopted was determined. The methodological option that best fits the characteristics of this research is bibliometrics [73,74]. This decision was agreed upon by evaluating the potential of scientometrics developed in the processes of locating, recording, identifying, and forecasting academic production [75]. In addition, what has been developed by other researchers in this method was taken as a reference as the backbone of this research [76].
More specifically, this research also includes the study of joint words [77], as well as other bibliometric indicators (h, g, hg, q2) [78]. The inclusion and analysis of these aspects makes it possible to obtain various conceptual maps that indicate the development and location of issues related to "collaborative learning" (COLE). It should also be noted that graphic design allows us to observe the evolution of COLE-related topics in WoS [79]. For this reason, the analysis of these aspects was considered key to the choice of research methodology.

3.2. Procedure and Data Analysis

It is worth mentioning in detail the steps that this research has been experiencing. Firstly, the choice of the database to be analyzed (WoS) was made. The Web of Science, owned by the company Clarivate Analytics, is the collection of databases of bibliographic references and citations from periodicals that collect information from 1900 to the present. The WoS is composed of the Core Collection which covers the Science, Social Science, and Arts and Humanities indexes, as well as the Proceedings of both Science and Social Science and Humanities along with tools for analysis and evaluation, such as the Journal Citation Report and Essential Science Indicators. Secondly, the key words to be analyzed were specified ("collaborative learning"). Thirdly, the search equation was elaborated ("collaborative learning" (TITLE)). Fourthly, the term was searched in the title of the various publications. As a result, a total of 3411 publications were initially collected. It is significant that the concept of collaborative learning has existed in the scientific literature since 1970. Therefore, we proceeded in this research with a diachronic perspective analyzing the 49-year-old literary volume, including 2019. In this sense, the publications related to 2020 (n = 67) were eliminated since they did not end the calendar year. Note that repeated documents or those that were wrongly indexed (n = 49) were also deleted. This represents a final analysis of 3295 documents. To reflect all the actions assumed in this study, a process based on the PRISMA protocol was followed (Figure 1).
As can be seen, a number of inclusion criteria were taken into account in the total number of documents submitted in the descriptive analysis of the scientific output. For this purpose, the program Analyze Results and Creation Citation Reports (tools integrated in the WoS platform), for academic performance, was used. These results were presented taking into account certain levels of inclusion (year of publication = all production except 2020; language ≥ 20; area of publication ≥ 200; type of documents ≥ 50; organizations ≥ 34; authors ≥ 23; sources of origin ≥ 50; countries ≥ 190; citation: the four most cited documents ≥ 390).
The SciMAT program ver.1.1.04 (Granada, Spain, 2016) is used to identify the scientific evolution of the term, taking into account the assessments given by specialists [80,81,82]. The phases followed in this analysis are (Figure 2):am
  • Detection of research topics: Of the 6189 keywords collected on the subject of study in WoS, a total of 5741 keywords were analyzed. This is due to the creation of a network of co-occurrence through nodes. Keywords are connected when two of these words co-appear in different scientific texts, generating a standardized network of co-words. Using the clustering algorithm, the research topics were located, thus showing the strongly related keywords. The keywords given by the authors and those created by WoS were used, according to the type of document. In addition, all the scientific production was analyzed to check that there were no repeated documents, and certain documents that appeared in the search that were not strictly related to the subject matter, using the IBM SPSS Statistics ver. 20 program (Armok, NY, USA, 2011), which, by means of the frequency tables, locates the repeated documents.
  • Representation of the research topic: For this purpose, a strategic diagram and a thematic network were used, formed by two dimensions (centrality and density), where the key words are shown in four sectors: Upper right sector, where the motor and fundamental topics in the research topic are located; upper left sector, where the connections are weak and they are nodes with little relevance in the topic; lower left sector, where the topics are relevant but they do not have a pressing development; and lower right sector, where the nodes lack development or relevance, although those that appear in that area can be emerging topics.
  • Location of thematic areas. This is determined by the chronological evolution shown by the nodes from one period to another. The strength of the relationship is based on the number of key words they have in common. The analysis begins in 1970 and ends in 2019. The periods established were P1 (1970–2006), P2 (2007–2011), P3 (2012–2015), and P4 (2016–2019).
  • Performance analysis. Each of the keywords has, in turn, a chain of connections that mark the trend of that node, offering data on the use that the scientific community makes of it. For this purpose, analysis protocols were established (Table 1).

4. Results

4.1. Scientific Production Performance

Research over time on collaborative learning was composed of 3295 documents. The evolution of the term in scientific production has been irregular. From 1970, when the first document was published in WoS, until 2001, scientific production was scarce. This evolution is not constant over time, given that there are years in which the scientific community has not produced content related to the topic. From 2002 to 2013, the scientific production has been growing constantly. In 2014, it breaks the upward trend, and will grow again in 2015. This year is when the highest production peak occurs. From 2016 to 2019, the production on collaborative learning has been gradually decreasing (Figure 3).
The language used by the researchers to show their scientific results is English, being very distant from the other languages (Table 2).
The main area of knowledge in which scientific findings about COLE are collected is Education Educational Research. The following knowledge areas are focused on the field of computing (Table 3).
There are even production levels, if you bear in mind the type of document used. In this case, the articles slightly exceed the communications (Table 4).
The main institution attending to the field of study presented is the UOC Universitat Oberta de Catalunya. Its level of production is slightly higher than that of the other institutions (Table 5).
In the studies on collaborative learning, two authors stand out above the rest, in terms of volume of production. These authors are Cabelle, S, and Jarvela, S. As can be seen in Table 6, there is not much distance, as far as production is concerned, with the rest of the authors.
The main source of production is Lecture Notes in Computer Science, which stands out considerably from other sources (Table 7).
The United States is the country with the highest volume of production on COLE. The next country is Spain, although its production level is far from the first (Table 8).
The most frequently cited document is that of Stahl, Koschmann, and Suther (2006), which presents a high number of citations, with a total of 658. It is closely followed by the manuscript of Kreijns, Kirschner, and Jochems (2003), with 635 citations. The rest of the documents are distant, in terms of the number of citations (Table 9).

4.2. Evolution of COLE’s Structure and Theme

The development of the keywords is evident, bearing in mind the established time intervals. In this case, it provides information on the keywords that are no longer used in the contiguous period, new keywords that appear in a certain period, and keywords that coincide between periods. It also shows the total number of keywords used in a given time period. As shown in Figure 4, the level of coincidence has been decreasing from the first time interval to the last one. In other words, the level of coincidence has gone from 37% to 29%. What we observed shows changes in the lines of study on COLE, so the focus of studies is likely to change in the coming years.
The analysis of the keywords used by the authors in their research, taking into account the established time intervals, provides information on the various bibliometric indices. In this case, the most relevant subjects with the best indicators are shown. The h index is a system that simultaneously measures the quality (based on the number of citations received) and the quantity of scientific output and is very useful for detecting the most outstanding research personnel within a knowledge area [88]. The g index is calculated from the distribution of citations received by the publications of a given researcher. It is similar to the h index, more complex in its calculation, but as it is larger and more variable, it allows us to distinguish between authors with a similar h index [89]. The hg index tries to avoid the great influence that a single publication with many citations can have on the g index [90]. In the first interval (1970–2006), the topic with the best bibliometric value is "collaborative-learning". In the second period (2007–2011), it is "environments". In the third period (2012–2015), it is "technology". Lastly, in the fourth period (2016–2019), it is "knowledge", followed very closely by "achievement". If the periods are analyzed as a whole, it can be seen that there is no continuous line in the field of study of COLE, and that there are changes in trends. The themes have been ordered according to index h. (Table 10).
  • The strategic diagrams by index h show the level of relevance and importance of the different themes. This was done by means of grouping techniques, bearing in mind Callon’s index. This value presents the level of connection of the various thematic networks, taking into account centrality and density. Centrality identifies the strength of association of external connections between themes. Density analyses the internal association force, identifying all the key words related to a given theme.
  • Bearing in mind the results achieved in the different diagrams (Figure 5), there is no theme that is repeated in all the established time intervals. In this case, the themes vary between the different periods. In the first period (1970–2006), only "students" appears as the driving theme, which is related to "performance", "mathematics", "work", "classroom", "environments", "motivation", and "achievement". In other words, the beginning of research on COLE focused on students.
  • In the following time frame, established between 2007 and 2011, the driving themes are "hand-heeds", related to "participatory-simulation" and "gestures"; and "self-efficacy", related to "collective-efficacy", "engagement", "beliefs", "classroom", "achievement", "performance", "mathematics", and "work". In this period, the focus of the study is on the self-efficacy of the method and the use of technological devices.
  • In the third period (2012–2015), the number of driving themes increases considerably with respect to the previous periods. In this case, the driving themes are "self-regulation", which is related to "social-shared-regulation", "instruction", "metacognition", "perspective", "strategies" " co-regulation", "motivation", and "self-regulated-learning"; "technology", which is linked to "design", "acceptance", "user-acceptance", "systems", "tools", "collaborative-learning", "education", and "information"; "performance", which is based on "conflict", "self-efficacy", "computer-mediated-communication", "interactive-learning-environment" "achievement", "impact", "science", and "group-decision-making"; "participation", which relates to "engagement", "efficacy", "interactive", "school", "visualization", "patterns", "issues", and "satisfaction"; and "knowledge-construction", which relates to "content-analysis", "scaffolding", "interaction-analysis", "project", "scripts", "on-line", "computer-supported-collaborative-learning", and "time". In this period, it can be seen that the focus of research is on more concrete aspects of learning. Examples of this are knowledge acquisition, self-regulation, and student involvement in the teaching and learning process. In addition, technology is beginning to be taken into account.
  • In the last period (2016–2019), the driving themes are "computer-mediated-communication", related to "self-efficacy", "satisfaction", "teaching/learning-strategies", "communities", "interactive-learning-environments", "learning-communities", "perspective", and "work"; "science’, linked to ’inquiry’, ’peer-learning’, ’gender’, ’environments’, ’game’, ’gender-differences’, ’scripts’, and ’knowledge-construction’; ’perceptions’, based on ’pedagogy’, ’educational-innovation’, ’networking-sites’, ’experiences’, ’university’, ’higher-education’, ’social-presence’, and ’acceptance’; "co-regulation", related to "group-engagement", "interplay", "self", "motivation", "video-data", "socially shared-regulation", "self-regulation", and "metacognition"; "support", linked to "participation", "computer-supported-collaborative-learning", "construction", "mobile-devices", "systems", "wiki", "moodle", and "quality"; and "achievement", based on "impact", "skills", "academic-performance", "classroom", "group-performance", "students", "meta-analysis", and "group-work". In this last period, it is also necessary to take into account the themes "innovation", "design", "patterns", "collaboration", and "communication", because its location in the diagram places it as an unknown subject. In other words, they may disappear from the context of study on COLE or be the next driving force. In this period, as can be seen, the focus of studies begins to be on the co-regulation of learning, student achievement, the field of science, students’ own perceptions, and the use of technological resources.

4.3. Evolutionary Development of COLE’s Themes

The development of the various themes presents the strength of the relationship between them. This connection occurs between the time intervals indicated above. The index used to identify the relational strength is the Jaccard index. This force is established by the number of keywords coinciding between the different themes. There are two types of connections that can be established: Conceptual connection, represented by a continuous line; and keyword connection, identified as a non-continuous line.
Bearing in mind what is established in Figure 6, it is possible to indicate that there is a conceptual gap. In other words, the same theme is not observed in the three time intervals. In addition, it can also be observed that there is no line of research that is settled in time, but rather that the field of study varies on the part of the scientific community. Another relevant aspect is the number of existing connections. The most common ones are established between the last and the penultimate period. There are also more thematic connections than conceptual ones. A thematic evolution can be seen, moving from a field of study focusing on students and the method itself, to the use of technological resources and specific and concrete aspects of learning, such as motivation, perception, knowledge, and self-regulation, among others. The thematic evolution confirms that there are constant changes in the lines of research of the scientific community.

4.4. Authors with the Highest Relevance Index

In relation to the authors, it is observed that Asensio-Pérez, J.I., Ruys, I., Redondo, M.A., and Hunger, A. are considered the driving forces in the field of COLE research. In addition, the authors Caballe, S., Collazos, C.A., and Fischer, F., should be taken into account, since they may be the driving forces in this field of study in the coming years (Figure 7).

5. Discussion

The new student’s profile, that is to say, a competent student, is forcing teachers to apply active teaching methods, i.e., requiring more active student’s involvement in the teaching–learning processes. In this case, teachers must become guides of this pedagogical act. The collaborative learning method is a clear example of an active teaching method [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17]. This teaching methodology requires two or more people who, thanks to the sharing of various resources and skills, can acquire the curricular elements proposed. This methodology encourages the development of other skills in students, such as interaction, communication, problem solving, motivation, sense of community, and autonomy, among other aspects [38,39,40,41,42,43,44,45,46,47,48,49]. In addition, the collaborative learning method promotes and facilitates the acquisition of knowledge in areas of study where sustainable development is essential [65,66,67,68,69].
In the present study, the collaborative learning method has been analyzed in the WoS database. The beginnings of this theme in the database go back to 1970, but it is not until 2005 that scientific production begins to grow. That is to say, it is when this teaching method begins to have relevance for the scientific community, mainly due to the high pedagogical value it has. Considering the four overall research objectives, we may argue that with regards to a) degree of performance of documents collected from collaborative learning, we have conducted the present research has made it possible to establish an X-ray of the profile presented by the studies related to the collaborative learning method by the scientific community. In this case, it can be said that they are presented in articles written in English by researchers from the United States. They are gathered in the area of knowledge called Education Educational Research. The institution with the greatest scientific production is the UOC Universitat Oberta de Catalunya. The most prolific authors are Cabelle, S., and Jarvela, S., although the most relevant authors are Asensio-Pérez, J.I., Ruys, I., Redondo, M.A., and Hunger, A. The main source of production is Lectura Notes in Computer Science. The most cited article is the work of Stahl, Koschmann, and Suther (2006), called Computer-Supported Collaborative Learning. These data show us that the interest in the collaborative learning method goes back several years, but it is in recent years where the interest has been growing considerably. These results may allow the scientific community to search, in a more efficient way, for studies related to collaborative learning.
The keywords of the analyzed manuscripts show us relevant and interesting information about the subject of the collaborative learning. In this case, we can see how the evolution of keywords during the different established time periods is decreasing. That is, as the years go by, the number of coincidences between the established periods is lower. This shows that there was a line of research established in the first time intervals, but currently new research perspectives are being established.
If we consider how the scientific development of the so-called collaborative learning has been identified (second research objective), we may say that the academic performance of the topics generated from these keywords shows that there is no coincidence in any of the established periods. That is, there are no themes that are repeated in the four periods. In the first period (1970–2006), the research was focused on the method itself, that is, on the collaborative learning. In the second period (2007–2011), on the learning environments. In the third period (2012–2015), on technology. In the fourth period (2016–2019), on knowledge. In other words, there is a variety of themes, all of them oriented to learning, to the environment where it takes place and to the technological resources.
Last but not least, with regards to the analysis of the most incidental aspects of collaborative learning and the value the most representative authors who are experts in the use of collaborative learning, we may consider the diagrams established and generated in each of the periods show us the really relevant topics for the educational community. In this case, in the first period (1970–2006), it was the students. In the following time frame (2007–2011), it was the portable resources and the self-efficacy of the training process.
In the third period (2012–2015), there was a change of trend, expanding the lines of research, oriented towards the acquisition of knowledge, self-regulation, and student’s involvement in learning. In the last period (2016–2019), the focus is more on the co-regulation of learning, on the use of technological resources, and on the educational achievements of the students themselves. As it can be seen, the focus has shifted from the students themselves to the various branches of knowledge. In other words, studies are based on learning skills to develop the competence of learning to learn. All of this is associated with the use of technological resources.
Thematic developments in adjacent periods confirm the results achieved previously. In this case, no solid line of research is shown on the collaborative learning method, there being a conceptual gap in the research field. What the thematic evolution offers is the appearance of new lines of inquiry as time goes by. All these data facilitate and provide detailed information on the most relevant lines of research and trends in this field of study. With this, the scientific community, interested in studies on collaborative learning, will know, in a more concise way, the most interesting aspects for the scientific community. It will identify the topics of study most analyzed by the researchers. In addition, it provides a clear and concise image of all the lines of study established in the various years. In doing so, it offers more detail on the studies carried out in recent years.

6. Conclusions

Finally, the conclusion that can be drawn about the use of collaborative learning is somehow at a turning point in the scientific field. Its scientific evolution, focused on its principles in the students themselves, has extended to other branches. Currently, studies are oriented towards technological resources, co-regulation, and the academic achievements of students. Furthermore, in the coming years, the terms innovation, design, patterns, collaboration, and communication will probably be the new lines of research in this field of study. For this reason, the degree of performance of documents shows the relevance of collaborative learning. More precisely, this research aims to provide the scientific community with the most representative aspects of COLE studies. In addition, the aim is to offer the educational community a more in-depth knowledge of this teaching method. It also tries to offer the latest trends.
On the other hand, considering the scientific development of the collaborative learning we have shown that academic performance proofs no coincidence in any established periods. However, the analysis of the most incidental aspects of the collaborative learning lets us be aware of how authors generate knowledge based on the diagrams shown.
The prospective of this research is to provide the scientific community with updated information on the collaborative learning method. It also aims to be a reference point for teachers from different educational stages, so that they can learn about the latest trends and the different pedagogical applications of this teaching method. Finally, it was also presented to show that the collaborative learning method promotes training in students to face sustainability.
The present investigation has several limitations, including the adequacy of the database. This requires an in-depth analysis, to identify those scientific productions not related to the subject of study. In this case, the volume of production is high. Another aspect is determining the time periods. The researchers chose to follow the criterion of quantity, trying to accumulate a similar number of productions in each of the time periods. Thirdly, the indicators established in the SciMAT v.1.1.04 (2016) program are set by the authors themselves. If these values are modified, the results present in this study may change. For new lines of research in the future, we propose to identify the collaborative learning method in specific educational branches, such as Mathematics or Social Sciences. In addition, an analysis of the term collaborative learning can be carried out in other databases, such as Scopus or Google Scholar.

Author Contributions

A.-J.M.-G.: Methodology, software, validation, investigation, writing—original draft preparation, and writing—review and editing; P.J.d.l.S.: Conceptualization, methodology, investigation, formal analysis, writing—original draft preparation, writing—review and editing, visualization, and supervision; M.L.P.-F.: Conceptualization, formal analysis, investigation, data curation, writing—original draft preparation, writing—review and editing, visualization, and supervision; R.S.C.: Software, validation, investigation, writing—original draft preparation, writing—review and editing, visualization, and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

The researchers of this study appreciate the support received by the AREA research group (HUM-672), from the University of Granada.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Martínez, S. Teaching innovation projects: Fundamental features to their on design, implementation and evaluation. Rev. Cienc. Pedagógicas Innovación 2019, 7, 95–103. [Google Scholar] [CrossRef]
  2. Supermane, S. Transformational leadership and innovation in teaching and learning activities: The mediation effect of knowledge management. Inf. Discov. Deliv. 2019, 47, 242–250. [Google Scholar] [CrossRef]
  3. Kars-Unluoglu, S. How do we educate future innovation managers? Insights on innovation education in MBA syllabi. Innov.-Manag. Policy Pract. 2016, 18, 74–98. [Google Scholar] [CrossRef]
  4. Goolsarran, N.; Hamo, C.E.; Lu, W.H. Using the jigsaw technique to teach patient safety. Med. Educ. Online 2020, 25, 1710325. [Google Scholar] [CrossRef] [Green Version]
  5. Killen, C.P. Three dimensions of learning: Experiential activity for engineering innovation education and research. Eur. J. Eng. Educ. 2015, 40, 476–498. [Google Scholar] [CrossRef]
  6. Li, G.; Wang, F. Research on art innovation teaching platform based on data mining algorithm. Clust. Comput. J. Neteworks Softw. Tools Appl. 2019, 22, 13867–13872. [Google Scholar] [CrossRef]
  7. Ho, P.A.; Girgis, C.; Rustad, J.K.; Noordsy, D.; Stern, T.A. Advancing the Mission of Consultation-Liaison Psychiatry Through Innovation in Teaching. Psychosomatics 2019, 60, 539–548. [Google Scholar] [CrossRef] [PubMed]
  8. Soltis, N.A.; McNeal, K.S.; Forbes, C.T.; Lally, D. The relationship between active learning, course innovation, and teaching Earth systems thinking: A structural equation modeling approach. Geosphere 2019, 15, 1703–1721. [Google Scholar] [CrossRef]
  9. Luque, A.M. Ways of otherness in an institutional history teaching innovation experiences for jurists and political scientist. E-Leg. Hist. Rev. 2019, 30, 1–20. [Google Scholar]
  10. Beekman, M.; Emani, V.K.; Wolford, R.; Hanson, K.; Wickham, G.; Aiyer, M. Patient Safety Morning Report: Innovation in Teaching Core Patient Safety Principles to Third-Year Medical Students. J. Med. Educ. Curric. Dev. 2019, 6. [Google Scholar] [CrossRef] [Green Version]
  11. Bravo, M.J.; Ortuno, M.A.; Valmana, A.; Vizcaino, J.; Rodríguez, R.; Ruiz, M.E.; Salazar, M.; Vallejo, G.; Osaba, M.E. IVRA: Romans, Visigoths and Byzantines. An experience of teaching innovation in the key of gender. Rev. Educ. Derecho 2019, 20, 1–34. [Google Scholar]
  12. Androutsos, A.; Brinia, V. Developing and Piloting a Pedagogy for Teaching Innovation, Collaboration, and Co-Creation in Secondary Education Based on Design Thinking, Digital Transformation, and Entrepreneurship. Educ. Sci. 2019, 9, 113. [Google Scholar] [CrossRef] [Green Version]
  13. Collier, M.; Trauer, E.; Perassi, R.; Costa, E. Interdisciplinarity, design thinking, and innovation in public spaces: A teaching experience in florianopolis botanical garden park. Risus J. Innov. Sustain. 2019, 10, 86–97. [Google Scholar] [CrossRef] [Green Version]
  14. Van Assche, N.; Fickl, S.; Francisco, H.; Gurzawska, K.; Milinkovic, I.; Navarro, J.M.; Torsello, F.; Thoma, D.S. Guidelines for development of Implant Dentistry in the next 10years regarding innovation, education, certification, and associations. Clin. Oral Implant. Res. 2018, 29, 568–575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Chou, C.M.; Shen, C.H.; Hsiao, H.C.; Shen, T.C. Factors influencing teachers’ innovative teaching behaviour with information and communication technology (ICT): The mediator role of organisational innovation climate. Educ. Psychol. 2019, 39, 65–85. [Google Scholar] [CrossRef]
  16. Campos, N.; Ramos, M.; Moreno-Guerrero, A.J. Virtual reality and motivation in the educational context: Bibliometric study of the last twenty years from Scopus. Alteridad Rev. Educ. 2020, 15, 47–60. [Google Scholar] [CrossRef]
  17. López, D.; Calonge, A.; Rodríguez, T.; Ros, G.; Lebron, J.A. Using Gamification in a Teaching Innovation Project at the University of Alcala: A New Approach to Experimental Science Practices. Electron. J. E-Learn. 2019, 17, 93–106. [Google Scholar] [CrossRef] [Green Version]
  18. Moreno-Guerrero, A.J.; Rodríguez-Jiménez, C.; Gómez-García, G.; Ramos, M. Educational Innovation in Higher Education: Use of Role Playing and Educational Video in Future Teachers’ Training. Sustainability 2020, 12, 2558. [Google Scholar] [CrossRef] [Green Version]
  19. Salas-Rueda, R.A. Use of the TPACK model as an innovation tool for the teaching-learning process on mathematics. Perspect. Educ. 2018, 57. [Google Scholar] [CrossRef]
  20. Hofmann, R.; Mercer, N. Teacher interventions in small group work in secondary mathematics and science lessons. Lang. Educ. 2016, 30, 400–416. [Google Scholar] [CrossRef]
  21. López, J.A.; López, J.; Moreno-Guerrero, A.J.; Pozo, S. Effectiveness of Innovate Educational Practices with Flipped Learning and Remote Sensing in Earth and Environmental Sciences—An Exploratory Case Study. Remonte Sens. 2020, 12, 897. [Google Scholar] [CrossRef] [Green Version]
  22. Kerhani, P.; Kaveh, M.H.; Faghih, S.; Salehi, M. Improving diet quality among adolescents, using health belief model in a collaborative learning context: A randomized field trial study. Health Educ. Res. 2019, 34, 279–288. [Google Scholar] [CrossRef] [Green Version]
  23. Acosta, R.; Martín-García, A.V.; Hernández, A. Use of the Collaborative Learning Methodologies with ICT: An analysis based on the teachers’ beliefs. Digit. Educ. Rev. 2019, 35, 309–323. [Google Scholar]
  24. Van Leeuwen, A.; Janssen, J. A systematic review of teacher guidance during collaborative learning in primary and secondary education. Educ. Res. Rev. 2019, 27, 71–89. [Google Scholar] [CrossRef]
  25. Isohatala, J.; Naykki, P.; Jarvela, S. Cognitive and Socio-Emotional Interaction in Collaborative Learning: Exploring Fluctuations in Students’ Participation. Scandinavian J. Educ. Res. 2019, 1–21. [Google Scholar] [CrossRef]
  26. Alghasab, M.; Hardman, J.; Handley, Z. Teacher-student interaction on wikis: Fostering collaborative learning and writing. Learn. Cult. Soc. Interact. 2019, 21, 10–20. [Google Scholar] [CrossRef]
  27. Voupala, E.; Naykki, P.; Isohatala, J.; Jarvela, S. Knowledge co-construction activities and task-related monitoring in scripted collaborative learning. Learn. Cult. Soc. Interact. 2019, 21, 234–249. [Google Scholar] [CrossRef]
  28. Maqtary, N.; Mohsen, A.; Bechkoum, K. Group Formation Techniques in Computer-Supported Collaborative Learning: A Systematic Literature Review. Technol. Knowl. Learn. 2019, 24, 169–190. [Google Scholar] [CrossRef]
  29. Jung, J.; Shin, Y.; Zumbach, J. The effects of pre-training types on cognitive load, collaborative knowledge construction and deep learning in a computer-supported collaborative learning environment. Interact. Learn. Environ. 2019, 1–13. [Google Scholar] [CrossRef]
  30. Boulton, H. Crossing boundaries: The affordances of new technologies in supporting a collaborative learning environment for doctoral students learning transnationally. Technol. Pedagog. Educ. 2019, 28, 255–267. [Google Scholar] [CrossRef]
  31. Hirsh, A.; Segolsson, M. Enabling teacher-driven school-development and collaborative learning: An activity theory-based study of leadership as an overarching practice. Educ. Manag. Adm. Leadersh. 2019, 47, 400–420. [Google Scholar] [CrossRef]
  32. Schnaubert, L.; Bodemer, D. Providing different types of group awareness information to guide collaborative learning. Int. J. Comput. Supported Collab. Learn. 2019, 14, 7–51. [Google Scholar] [CrossRef]
  33. Williams, E.A.; Zwolak, J.P.; Dou, R.; Brewe, E. Linking engagement and performance: The social network analysis perspective. Phys. Rev. Phys. Educ. Res. 2019, 15, 1–15. [Google Scholar] [CrossRef] [Green Version]
  34. Gomez, L.F. Intention and Pedagogical Competence: Use of Collaborative Learning in the Subject of Mathematics in Secondary School. Propósitos Represent. 2016, 4, 157–179. [Google Scholar] [CrossRef] [Green Version]
  35. Zhang, X.; Meng, Y.; Ordóñez, P.; Sun, Y. Learning analytics in collaborative learning supported by Slack: Fromthe perspective of engagement. Comput. Hum. Behav. 2019, 92, 625–633. [Google Scholar] [CrossRef]
  36. Hautala, J.; Schmidt, S. Learning across distances: An international collaborative learning project between Berlin and Turku. J. Geogr. High. Educ. 2019, 43, 181–200. [Google Scholar] [CrossRef]
  37. Moreno-Guerrero, A.J.; Rondón, M.; Martínez, N.; Rodríguez-García, A.M. Collaborative Learning Based on Harry Potter for Learning Geometric Figures in the Subject of Mathematics. Mathematics 2020, 8, 369. [Google Scholar] [CrossRef] [Green Version]
  38. Hargreaves, E.; Elhawary, D.; Mahgoub, M. ‘One girl had a different idea’: Children’s perspectives on learning and teaching models in the traditional classroom. Education 3-13 2020, 48, 97–99. [Google Scholar] [CrossRef]
  39. Simons, M.; Baeten, M.; Vanhees, C. Team Teaching During Field Experiences in Teacher Education: Investigating Student Teachers’ Experiences with Parallel and Sequential Teaching. J. Teach. Educ. 2020, 71, 24–40. [Google Scholar] [CrossRef]
  40. Tissenbaum, M. I see what you did there! Divergent collaboration and learner transitions from unproductive to productive states in open-ended inquiry. Comput. Educ. 2020, 145, 103739. [Google Scholar] [CrossRef]
  41. Domingo-Coscollola, M.; Bosco, A.; Carrasco, S.; Sánchez, J.A. Fostering teacher’s digital competence at university: The perception of students and teachers. Rev. Investig. Educ. 2020, 38, 167–182. [Google Scholar] [CrossRef]
  42. Hsieh, Y.C. Learner interactions in face-to-face collaborative writing with the support of online resources. RECALL 2020, 32, 85–105. [Google Scholar] [CrossRef]
  43. Troussas, C.; Krouska, A.; Sgouropoulou, C. Collaboration and fuzzy-modeled personalization for mobile game based learning in higher education. Comput. Educ. 2020, 144, 103698. [Google Scholar] [CrossRef]
  44. Chatterjee, R.; Correia, A.P. Online Students’ Attitudes toward Collaborative Learning and Sense of Community. Am. J. Distance Educ. 2019, 34, 53–68. [Google Scholar] [CrossRef]
  45. Wilson, K.F.; Wilson, K. Collaborate to graduate: What works and why? High. Educ. Res. Dev. 2019, 38, 1504–1518. [Google Scholar] [CrossRef]
  46. Asino, T.I.; Pulay, A. Student Perceptions on the Role of the Classroom Environment on Computer Supported Collaborative Learning. Techtrends 2019, 63, 179–187. [Google Scholar] [CrossRef]
  47. Volet, S.; Seghezzi, C.; Ritchie, S. Positive emotions in student-led collaborative science activities: Relating types and sources of emotions to engagement in learning. Stud. High. Educ. 2019, 44, 1734–1746. [Google Scholar] [CrossRef]
  48. Bers, M.U.; González-González, C.; Armas-Torres, U. Coding as a playground: Promoting positive learning experiences in childhood classrooms. Comput. Educ. 2019, 138, 130–145. [Google Scholar] [CrossRef]
  49. Rojprasert, S.; Neanchaleay, J.; Boonlue, S.; Sinlarat, P. Designing and implementing constructionist learning in a blended advertising photography course. Int. J. Technol. Enhanc. Learn. 2020, 12, 20–37. [Google Scholar] [CrossRef]
  50. Sobocinski, M.; Jarvela, S.; Malmberg, J.; Dindar, M.; Isosalo, A.; Noponen, K. How does monitoring set the stage for adaptive regulation or maladaptive behavior in collaborative learning? Metacognitive Learn. 2020, 29, 99–127. [Google Scholar] [CrossRef]
  51. Dindar, M.; Alikhani, I.; Malmberg, J.; Jarvela, S.; Seppanen, T. Examining shared monitoring in collaborative learning: A case of a recurrence quantification analysis approach. Comput. Hum. Behav. 2019, 100, 335–344. [Google Scholar] [CrossRef]
  52. Salam, M.; Farooq, M.S. Does sociability quality of web-based collaborative learning information system influence students’ satisfaction and system usage? Int. J. Educ. Technol. High. Educ. 2020, 17, 26–39. [Google Scholar] [CrossRef]
  53. Ting, Y.L.; Tai, Y.M.; Chen, J.H. Transformed telepresence and its association with learning in computer-supported collaborative learning: A case study in English learning and its evaluation. Interact. Learn. Environ. 2017, 25, 382–396. [Google Scholar] [CrossRef]
  54. Jarvenoja, H.; Naykki, P.; Tormanen, T. Emotional regulation in collaborative learning: When do higher education students activate group level regulation in the face of challenges? Stud. High. Educ. 2019, 44, 1747–1757. [Google Scholar] [CrossRef]
  55. Zheng, L.Q.; Zhang, X.; Gyasi, J.F. A literature review of features and trends of technology-supported collaborative learning in informal learning settings from 2007 to 2018. J. Comput. Educ. 2019, 6, 529–561. [Google Scholar] [CrossRef]
  56. Sung, Y.T.; Yang, J.M. The Effects of Mobile-Computer-Supported Collaborative Learning: Meta-Analysis and Critical Synthesis. Rev. Educ. Res. 2017, 87, 768–805. [Google Scholar] [CrossRef] [Green Version]
  57. Rabu, S.N.A.; Badlishah, N.S. Levels of Students’ Reflective Thinking Skills in a Collaborative Learning Environment Using Google Docs. Educ. Educ. Res. 2020, 64, 533–541. [Google Scholar] [CrossRef]
  58. Nam, C.W. The effects of digital storytelling on student achievement, social presence, and attitude in online collaborative learning environments. Interact. Learn. Environ. 2017, 25, 412–427. [Google Scholar] [CrossRef]
  59. Jeong, H.; Hmelo-Silver, C.E.; Kihyun, J. Ten years of Computer-Supported Collaborative Learning: A meta-analysis of CSCL in STEM education during 2005–2014. Educ. Res. Rev. 2019, 28, 100284. [Google Scholar] [CrossRef]
  60. De Hei, M.; Tabacaru, C.; Sjoer, E.; Rippe, R.; Walenkamp, J. Developing Intercultural Competence Through Collaborative Learning in International Higher Education. J. Stud. Int. Educ. 2020, 24, 190–211. [Google Scholar] [CrossRef] [Green Version]
  61. Romeike, B.F.M.; Fischer, M. Buzz groups facilitate collaborative learning and improve histopathological competencies of students. Clin. Neuropathol. 2019, 38, 285–293. [Google Scholar] [CrossRef] [PubMed]
  62. Tan, T.A.G.; Vicente, A.J. An innovative experiential and collaborative learning approach to an undergraduate marketing management course: A case of the Philippines. Int. J. Manag. Educ. 2019, 17, 100309. [Google Scholar] [CrossRef]
  63. Zhang, S.; Wen, Y.; Liu, Q.T. Exploring student teachers’ Social knowledge construction behaviors and collective agency in an online collaborative learning environment. Interact. Learn. Environ. 2019, 1–13. [Google Scholar] [CrossRef]
  64. Vega, N.; Stanfield, J.; Mitra, S. Investigating the impact of Computer Supported Collaborative Learning (CSCL) to help improve reading comprehension in low performing urban elementary schools. Educ. Inf. Technol. 2019, 25, 1–14. [Google Scholar] [CrossRef] [Green Version]
  65. Blau, I.; Shamir-Inbal, T.; Hadad, S. Digital collaborative learning in elementary and middle schools as a function of individualistic and collectivistic culture: The role of ICT coordinators’ leadership experience, students’ collaboration skills, and sustainability. J. Comput. Assist. Learn. 2020. [Google Scholar] [CrossRef]
  66. Silva, M.F.; Malheiro, B.; Guedes, P.; Duarte, A.; Ferreira, P. Collaborative Learning with Sustainability-driven Projects: A Summary of the EPS@ISEP Programme. Int. J. Eng. Pedagog. 2018, 8, 106–130. [Google Scholar] [CrossRef]
  67. Augustin, S. The Burnout Phenomenon: A Comparative Study of Student Attitudes Toward Collaborative Learning and Sustainability. J. Inter. Des. 2014, 39, 17–31. [Google Scholar] [CrossRef]
  68. Schechter, C.; Ganon, S. Learning from success: Exploring the sustainability of a collaborative learning initiative. J. Educ. Adm. 2012, 50, 732–754. [Google Scholar] [CrossRef]
  69. Kallstrom, H.N.; Ljung, M. Social sustainability and collaborative learning. Ambio 2005, 34, 376–382. [Google Scholar] [CrossRef]
  70. López-Belmonte, J.; Moreno-Guerrero, A.J.; López, J.A.; Pozo, S. Analysis of the Productive, Structural, and Dynamic Development of Augmented Reality in Higher Education Research on the Web of Science. Appl. Sci. 2019, 9, 5306. [Google Scholar] [CrossRef] [Green Version]
  71. López-Belmonte, J.; Segura-Robles, A.; Moreno-Guerrero, A.J.; Parra-González, M.E. Machine Learning and Big Data in the Impact Literature. A Bibliometric Review with Scientific Mapping in Web of Science. Symmetry 2020, 12, 495. [Google Scholar] [CrossRef] [Green Version]
  72. Rodríguez-García, A.M.; López-Belmonte, J.; Agreda, M.; Moreno-Guerrero, A.J. Productive, Structural and Dynamic Study of the Concept of Sustainability in the Educational Field. Sustainability 2019, 11, 5613. [Google Scholar] [CrossRef] [Green Version]
  73. Moreno-Guerrero, A.J. Estudio bibliométrico de la producción científica en Web of Science: Formación Profesional y blended learning. PIXEL-BIT: Rev. Medios Educ. 2019, 56, 149–168. [Google Scholar] [CrossRef]
  74. Moreno-Guerrero, A.J. Estudio bibliométrico de la producción científica sobre la Inspección Educativa. REICE Rev. Iberoam. Sobre Calid. Efic. Cambio Educ. 2019, 17, 23–40. [Google Scholar] [CrossRef]
  75. Martínez, M.A.; Cobo, M.J.; Herrera, M.; Herrera, E. Analyzing the scientific evolution of social work using science mapping. Res. Soc. Work Pract. 2015, 25, 257–277. [Google Scholar] [CrossRef]
  76. Moral-Muñoz, J.A.; Herrera-Viedma, E.; Santisteban-Espejo, A.; Cobo, M.J. Software tools for conducting bibliometric analysis in science: An up-to-date review. Prof. Inf. 2020, 29. [Google Scholar] [CrossRef] [Green Version]
  77. Hirsch, J.E. An index to quantify an individual’s scientific research output. Proc. Natl. Acad. Sci. USA 2005, 102, 16569–16572. [Google Scholar] [CrossRef] [Green Version]
  78. Cobo, M.J.; López, A.G.; Herrera, E.; Herrera, F. Science mapping software tools: Review, analysis, and cooperative study among tools. J. Am. Soc. Inf. Sci. Technol. 2011, 62, 1382–1402. [Google Scholar] [CrossRef]
  79. López-Robles, J.R.; Otegi-Olaso, J.R.; Porto, I.; Cobo, M.J. 30 years of intelligence models in management and business: A bibliometric review. Int. J. Inf. Manag. 2019, 48, 22–38. [Google Scholar] [CrossRef]
  80. Montero-Díaz, J.; Cobo, M.J.; Gutiérrez-Salcedo, M.; Segado-Boj, F.; Herrera-Viedma, E. Mapeo científico de la Categoría «Comunicación» en WoS (1980–2013). Comunicar 2018, 26, 81–91. [Google Scholar] [CrossRef] [Green Version]
  81. Porter, A.L.; Kongthon, A.; Lu, J.-C.C. Research profiling: Improving the literature review. Scientometrics 2002, 53, 351–370. [Google Scholar] [CrossRef]
  82. Martinez, H.; Jaime, A.; Camacho, J. Relative absorptive capacity: A research profiling. Scientometrics 2012, 92, 657–674. [Google Scholar] [CrossRef]
  83. Hinojo-Lucena, F.J.; Dúo-Terrón, P.; Ramos Navas-Parejo, M.; Rodríguez-Jiménez, C.; Moreno-Guerrero, A.J. Scientific Performance and Mapping of the Term STEM in Education on the Web of Science. Sustainability 2020, 12, 2279. [Google Scholar] [CrossRef] [Green Version]
  84. Stahl, G.; Koschmann, T.; Suthers, D.D. Computer-Supported Collaborative Learning. Camb. Handb. Learn. Sci. 2006, 1, 409–425. [Google Scholar]
  85. Kreijns, K.; Kirschner, P.A.; Jochems, W. Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: A review of the research. Comput. Hum. Behav. 2003, 19, 335–353. [Google Scholar] [CrossRef] [Green Version]
  86. Alavi, M. Computer-Mediated Collaborative Learning. An empirical evaluation. MIS Q. 1994, 18, 159–174. [Google Scholar] [CrossRef]
  87. So, H.J.; Brush, T.A. Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors. Comput. Educ. 2006, 46, 71–95. [Google Scholar] [CrossRef]
  88. Hu, G.Y.; Wang, L.; Ni, R.; Liu, W.S. Which h-index? An exploration within the Web of Science. Scientometrics 2020, 123, 1225–1233. [Google Scholar] [CrossRef]
  89. Bertoli-Barsotti, L. Normalizing the g-index. Scientometrics 2016, 106, 645–655. [Google Scholar] [CrossRef]
  90. Alonso, S.; Cabrerizo, F.J.; Herrera-Viedma, E.; Herrera, F. hg-index: A new index to characterize the scientific output of researchers based on the h- and g-indices. Scientometrics 2010, 82, 391–400. [Google Scholar] [CrossRef] [Green Version]
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Figure 1. Flowchart according to the PRISMA Declaration.
Figure 1. Flowchart according to the PRISMA Declaration.
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Figure 2. Phases of co-word analysis using SciMAT. Recovered from [83].
Figure 2. Phases of co-word analysis using SciMAT. Recovered from [83].
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Figure 3. Evolution of the volume of production on collaborative learning.
Figure 3. Evolution of the volume of production on collaborative learning.
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Figure 4. Continuity of keywords between contiguous intervals.
Figure 4. Continuity of keywords between contiguous intervals.
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Figure 5. COLE’s h-index strategy diagram; (a) range 1970-2006; (b) range 2007–2011; (c) range 2012–2015; (d) range 2016–2019.
Figure 5. COLE’s h-index strategy diagram; (a) range 1970-2006; (b) range 2007–2011; (c) range 2012–2015; (d) range 2016–2019.
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Figure 6. Thematic evolution by h-index.
Figure 6. Thematic evolution by h-index.
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Figure 7. Diagram of authors producing COLE.
Figure 7. Diagram of authors producing COLE.
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Table
Table 1. Production indicators and inclusion criteria.
Table 1. Production indicators and inclusion criteria.
ConfigurationValues
Analysis unitKeywords authors, keywords WoS
Frequency thresholdKeywords: P1 = (2), P2 = (4), P3 = (4), P4 = (4)
Authors: PX = (4)
Network typeCo-occurrence
Co-occurrence union value thresholdKeywords: P1 = (2), P2 = (2), P3 = (2), P4 = (2), P5 = (2)
Authors: PX = (4)
Normalization measureEquivalence index
Clustering algorithmMaximum size: 9; Minimum size: 3
Evolutionary measureJaccard index
Overlapping measureInclusion Rate
Table
Table 2. Language used in scientific production.
Table 2. Language used in scientific production.
LanguagesCOLE (Number of Publications)
English3180
Spanish123
Portuguese25
Table
Table 3. Areas of knowledge.
Table 3. Areas of knowledge.
Areas of KnowledgeCOLE (Number of Publications)
Education Educational Research1659
Computer Science Interdisciplinary Applications576
Computer Science Information Systems469
Computer Science Theory Methods416
Computer Science Artificial Intelligence324
Education Scientific Disciplines317
Table
Table 4. Type of document.
Table 4. Type of document.
Document TypesCOLE (Number of Publications)
Article1625
Proceedings paper1535
Book Chapter151
Meeting abstract94
Editorial Material71
Table
Table 5. Institutions.
Table 5. Institutions.
OrganizationsCOLE (Number of Publications)
UOC Universitat Oberta de Catalunya43
Nanyang Technological University39
Nanyang Technologucal University National Institute of Education NIE Singapore39
Utrecht University38
University of Oulu35
Table
Table 6. Most prolific authors.
Table 6. Most prolific authors.
AuthorsCOLE (Number of Publications)
Cabelle, S.27
Jarvela, S.27
Hayashi, Y.24
Kirschiner. P.A.24
Table
Table 7. Main sources of production on collaborative learning.
Table 7. Main sources of production on collaborative learning.
Source TitlesCOLE (Number of Publications)
Lecture Notes in Computer Science151
Computers Education76
Computers in Human Behavior73
Procedia Social and Behavioral Sciences56
Table
Table 8. Country.
Table 8. Country.
CountriesCOLE (Number of Publications)
United States700
Spain354
China299
Japan196
Table
Table 9. Collaborative learning (COLE): Most cited articles.
Table 9. Collaborative learning (COLE): Most cited articles.
ReferenceCitations
[84]658
[85]635
[86]399
[87]391
Table
Table 10. Thematic performance in COLE.
Table 10. Thematic performance in COLE.
Interval 1970–2006
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Collaborative-learning30162419.6241153
Students11101110.4923.451053
CSCL159119.9525.461609
Collaboration10797.9415.87821
Science44448226
Discourse222211.6671
CSCLIP3232.457.7536
Interval 2007–2011
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Enviroments53264433.8235.692018
Collaborative-learning71204329.3334.931874
Self-efficacy12101210.9528.28784
Scripts13101210.9524.08726
Framework14101210.9518.17627
Face-to-face12101110.4920.25599
Learing17686.938.1277
Internet444410.5879
Semantic-web22224.2413
Handhelds41111.412
Reform31112.245
Interval 2012–2015
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Technology67193124.2726.151117
Performance23122115.8721.07458
Knowledge-contruction26112014.8315.2427
Self-regulation15101411.8320.74387
Students19101713.0417.89546
Knowledge16118.1210.1163
Higher-education146107.7511.22111
E-learning16697.358.8388
Enviroments126118.1211.49212
Support7676.4810.39111
Participation105107.0711.83336
Collaboration215107.079.22103
Competence4343.466.4622
Social-media4232.457.4857
ICT4222411
Mobile-learning4232.456.9335
Interval 2016–2019
DenominationWorksIndex hIndex gIndex hgIndex q2Citations
Knowledge84111914.4617.23492
Achievement34101411.8312.25254
Co-regulation187108.379.17118
Support247118.779.17137
Facebook186107.757.75101
Performance16686.938.1279
Computer-mediated-communication9676.4812.49130
Perceptions24586.326.3272
Science15374.585.4853
Collaboration15333320
Patterns9364.245.4839
Design6333650
Peer3232.453.469
Innovation5242.834.917
Communication411111

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Moreno-Guerrero, A.-J.; Jurado de los Santos, P.; Pertegal-Felices, M.L.; Soler Costa, R. Bibliometric Study of Scientific Production on the Term Collaborative Learning in Web of Science. Sustainability 2020, 12, 5649. https://0-doi-org.brum.beds.ac.uk/10.3390/su12145649

AMA Style

Moreno-Guerrero A-J, Jurado de los Santos P, Pertegal-Felices ML, Soler Costa R. Bibliometric Study of Scientific Production on the Term Collaborative Learning in Web of Science. Sustainability. 2020; 12(14):5649. https://0-doi-org.brum.beds.ac.uk/10.3390/su12145649

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Moreno-Guerrero, Antonio-José, Pedro Jurado de los Santos, María Luisa Pertegal-Felices, and Rebeca Soler Costa. 2020. "Bibliometric Study of Scientific Production on the Term Collaborative Learning in Web of Science" Sustainability 12, no. 14: 5649. https://0-doi-org.brum.beds.ac.uk/10.3390/su12145649

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